test gradio

app.py

@@ -13,7 +13,6 @@ login(token=token)
 model_path = 'stabilityai/stable-diffusion-3.5-large'
 ip_adapter_path = './ip-adapter.bin'
 image_encoder_path = "google/siglip-so400m-patch14-384"
-ref_img_path = './assets/1.jpg'  # Reference image path
 
 # Load SD3.5 pipeline and components
 transformer = SD3Transformer2DModel.from_pretrained(
@@ -31,43 +30,37 @@ pipe.init_ipadapter(
 
 
 @gr.Interface()
-def gui_generation(prompt: str, negative_prompt: str, ipadapter_scale: float, num_imgs: int):
+def gui_generation(image: Image, style_image: Image):
     """
-    Generate images based on prompt, negative prompt, and IP-Adapter scale.
+    Generate an image based on input and style images.
     """
-    ref_img = Image.open(ref_img_path).convert('RGB')  # Load reference image
     generator = torch.Generator("cuda").manual_seed(42)  # Reproducibility
 
-    images = []
-    for _ in range(num_imgs):
-        output = pipe(
-            width=1024,
-            height=1024,
-            prompt=prompt,
-            negative_prompt=negative_prompt,
-            num_inference_steps=24,
-            guidance_scale=5.0,
-            generator=generator,
-            clip_image=ref_img,
-            ipadapter_scale=ipadapter_scale,
-        ).images[0]
-        images.append(output)
-    return images
+    output = pipe(
+        width=1024,
+        height=1024,
+        prompt="",
+        negative_prompt="",
+        num_inference_steps=24,
+        guidance_scale=5.0,
+        generator=generator,
+        clip_image=style_image,
+        ipadapter_scale=0.5,
+    ).images[0]
+    return output
 
 
 # Gradio UI elements
-prompt_box = gr.Textbox(label="Prompt", placeholder="Enter your generation prompt here")
-negative_prompt_box = gr.Textbox(label="Negative Prompt", placeholder="e.g., lowres, worst quality")
-ipadapter_slider = gr.Slider(0.1, 1.0, value=0.5, step=0.1, label="IP-Adapter Scale")
-number_slider = gr.Slider(1, 5, value=1, step=1, label="Number of Images")
-gallery = gr.Gallery(label="Generated Images", columns=[3], rows=[1], object_fit="contain", height="auto")
+image_input = gr.Image(type="pil", label="Input Image")
+style_image_input = gr.Image(type="pil", label="Style Image")
+output_image = gr.Image(label="Generated Image")
 
 interface = gr.Interface(
     gui_generation,
-    inputs=[prompt_box, negative_prompt_box, ipadapter_slider, number_slider],
-    outputs=gallery,
-    title="Stable Diffusion 3.5 Image Generation with IP-Adapter",
-    description="Generate high-quality images with Stable Diffusion 3.5 Large and IP-Adapter guidance."
+    inputs=[image_input, style_image_input],
+    outputs=output_image,
+    title="Image Generation with Style Image",
+    description="Upload an input image and a style image to generate a new image based on the style."
 )
 
-interface.launch()
+interface.launch()